// Copyright 2010-2025 Google LLC
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
//     http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.

using System;
using Google.OrTools.Sat;
using Google.OrTools.Util;

public class VarArraySolutionPrinter : CpSolverSolutionCallback
{
    public VarArraySolutionPrinter(IntVar[] variables)
    {
        variables_ = variables;
    }

    public override void OnSolutionCallback()
    {
        {
            foreach (IntVar v in variables_)
            {
                Console.Write(String.Format("{0}={1} ", v.ToString(), Value(v)));
            }
            Console.WriteLine();
        }
    }

    private IntVar[] variables_;
}

public class ChannelingSampleSat
{
    static void Main()
    {
        // Create the CP-SAT model.
        CpModel model = new CpModel();

        // Declare our two primary variables.
        IntVar x = model.NewIntVar(0, 10, "x");
        IntVar y = model.NewIntVar(0, 10, "y");

        // Declare our intermediate boolean variable.
        BoolVar b = model.NewBoolVar("b");

        // Implement b == (x >= 5).
        model.Add(x >= 5).OnlyEnforceIf(b);
        model.Add(x < 5).OnlyEnforceIf(b.Not());

        // Create our two half-reified constraints.
        // First, b implies (y == 10 - x).
        model.Add(y == 10 - x).OnlyEnforceIf(b);
        // Second, not(b) implies y == 0.
        model.Add(y == 0).OnlyEnforceIf(b.Not());

        // Search for x values in increasing order.
        model.AddDecisionStrategy(new IntVar[] { x }, DecisionStrategyProto.Types.VariableSelectionStrategy.ChooseFirst,
                                  DecisionStrategyProto.Types.DomainReductionStrategy.SelectMinValue);

        // Create the solver.
        CpSolver solver = new CpSolver();

        // Force solver to follow the decision strategy exactly.
        // Tell the solver to search for all solutions.
        solver.StringParameters = "search_branching:FIXED_SEARCH, enumerate_all_solutions:true";

        VarArraySolutionPrinter cb = new VarArraySolutionPrinter(new IntVar[] { x, y, b });
        solver.Solve(model, cb);
    }
}
